In this age, it is a shame that camera operators may need to review hours and hours of video feed or the fact that already installed cameras are only recording when they can be doing much more.

What is the unmet need in society that your idea will fulfill ?

Cameras and camera feeds that don't fulfill their purpose (for e.g security) or become un-feasible in terms of huge video output that needs to be analyzed by a human operator or analyzed on the cloud for which high bandwidth is required

Who needs it ? How many would benefit ?

Anywhere where cameras may be deployed and object detection may be needed from their video feed. Security areas, agriculture, robotics, autonomous driving, UAVs, Planetary rovers, manufacturing, helping blind people navigate.

How will the solution works

An FPGA that runs an object detection and localization algorithm with optimization, running it ideally at lower power and faster speed than a traditional system, deployed with a camera or a network of cameras connected via LAN

Who are your competitors ? How is your solution different

DeepLens, Mars Science Laboratory. Deep Cognition, TensorCam, FLIR
Different is that it is indigenous and FPGA-based, other solutions are mostly ASIC-based and hence prone to becoming obsolete